Recent Advance in Diagnostic Oral Medicine – A Review


Authors : Dr. K. V. Vijila; Dr. Priya Ramani; Dr. Mohamed Yasin; Dr. Nithish Kumar; Dr. Mohammed Alia Ruqsana

Volume/Issue : Volume 9 - 2024, Issue 12 - December

Google Scholar : https://tinyurl.com/34mpb83d

Scribd : https://tinyurl.com/yc3tyxmn

DOI : https://doi.org/ 10.5281/zenodo.14558001

Abstract : Oral medicine plays a pivotal role in diagnostic decision-making and the field has witnessed significant advancements over time, revolutionizing the way oral diseases are diagnosed and managed. Recent advancements in diagnostic oral medicine offer promising solutions for early detection and accurate diagnosis. These innovations include the use of salivary biomarkers, advanced imaging technologies, and artificial intelligence (AI). Early detection is crucial for improving patient outcomes. Saliva-based biomarkers, such as miRNAs and proteins, provide a non-invasive method for early detection. Imaging techniques like auto fluorescence imaging, Raman spectroscopy, and optical coherence tomography enhances the visualization of abnormal tissues. AI-powered tools, particularly deep learning algorithms, can analyze images and data to improve diagnostic accuracy. By combining these technologies, we can achieve earlier detection, more accurate diagnosis, and personalized treatment plans for oral cancer patients.

Keywords : Oral cancer, Biomarkers, Artificial Intelligence, Nanotechnology, Chemiluminescence, Brush Biopsy.

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Oral medicine plays a pivotal role in diagnostic decision-making and the field has witnessed significant advancements over time, revolutionizing the way oral diseases are diagnosed and managed. Recent advancements in diagnostic oral medicine offer promising solutions for early detection and accurate diagnosis. These innovations include the use of salivary biomarkers, advanced imaging technologies, and artificial intelligence (AI). Early detection is crucial for improving patient outcomes. Saliva-based biomarkers, such as miRNAs and proteins, provide a non-invasive method for early detection. Imaging techniques like auto fluorescence imaging, Raman spectroscopy, and optical coherence tomography enhances the visualization of abnormal tissues. AI-powered tools, particularly deep learning algorithms, can analyze images and data to improve diagnostic accuracy. By combining these technologies, we can achieve earlier detection, more accurate diagnosis, and personalized treatment plans for oral cancer patients.

Keywords : Oral cancer, Biomarkers, Artificial Intelligence, Nanotechnology, Chemiluminescence, Brush Biopsy.

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